Efficient Multi-image Correspondences for On-line Light Field Video Processing

Light field videos express the entire visual information of an animated scene, but their shear size typically makes capture, processing and display an off‐line process, i. e., time between initial capture and final display is far from real‐time. In this paper we propose a solution for one of the key...

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Bibliographic Details
Published in:Computer graphics forum Vol. 35; no. 7; pp. 401 - 410
Main Authors: Dąbała, Ł., Ziegler, M., Didyk, P., Zilly, F., Keinert, J., Myszkowski, K., Seidel, H.-P., Rokita, P., Ritschel, T.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.10.2016
Subjects:
Algorithms
Analysis
Arrays
Cameras
Categories and Subject Descriptors (according to ACM CCS)
Computer graphics
Digital video
I.4.8 [Image processing and Computer Vision]: Scene Analysis- Shape
Light
Matching
Reconstruction
Shear
Studies
Video
Video data
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary:Light field videos express the entire visual information of an animated scene, but their shear size typically makes capture, processing and display an off‐line process, i. e., time between initial capture and final display is far from real‐time. In this paper we propose a solution for one of the key bottlenecks in such a processing pipeline, which is a reliable depth reconstruction possibly for many views. This is enabled by a novel correspondence algorithm converting the video streams from a sparse array of off‐the‐shelf cameras into an array of animated depth maps. The algorithm is based on a generalization of the classic multi‐resolution Lucas‐Kanade correspondence algorithm from a pair of images to an entire array. Special inter‐image confidence consolidation allows recovery from unreliable matching in some locations and some views. It can be implemented efficiently in massively parallel hardware, allowing for interactive computations. The resulting depth quality as well as the computation performance compares favorably to other state‐of‐the art light field‐to‐depth approaches, as well as stereo matching techniques. Another outcome of this work is a data set of light field videos that are captured with multiple variants of sparse camera arrays.
Bibliography:ArticleID:CGF13037
istex:97B172E4CF7B9B016AAC643801DBEA7B8BE406E3
ark:/67375/WNG-1LQ32FH6-Q
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.13037